Comments (9)
Sure, I can take a look at this.
By the way, is there any reason to not support Julia 0.2 right now? REQUIRE currently has julia 0.3-
.
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Yes, we should support Julia 0.2 as well. It is just my bad habit to work only with the latest build. Let's change REQUIRE in the next commit.
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@StefanKarpinski, just to verify: does the Pkg code care if supported versions of a package are sequential?
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If it does, we can just clear the old versions from METADATA.
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It won't let you use it to tag things non-sequentially, but if you tag by hand, it will work. You can also clear older versions.
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I renamed autodiff
to something more descriptive and added a few tests for this.
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That's great Miles, the dual_fad
name that you chose seems better indeed. Thanks for adding the tests! Shall we close this issue?
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Sure
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@mlubin, following your preferred style of your code, I generalized the interface and put it in the api.jl
file. Your code is nearly intact, I only had to make a couple of arguments optional so that they can interact with the generic API functions. Things start looking much more functional now... I also made tensor FAD possible, but will need some more work to overload more functions other than +,-,* (will do this).
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Related Issues (20)
- Rationals and Modulo
- `NaNMath` (and `SpecialFunctions`) as extensions? HOT 5
- Broken external link
- `construct_seeds` for types where `typeof(one(T)) !=T` is broken HOT 1
- incorrect 2nd derivative of complex exponential HOT 2
- Can you take derivative of complicated function whose symbolic form is not explicit or not known?
- Cancellation with sparse arrays HOT 5
- Implement hessian! for scalar x
- Implement gammalogccdf for ForwardDiff HOT 1
- `ForwardDiff.jacobian` throws error for `fft` HOT 1
- Correctly forming nested dual numbers. HOT 8
- Derivative of a function of derivatives HOT 7
- Symbolics.jl compatibility HOT 1
- Support derivative(f, ::Complex)
- `ForwardDiff` fails to compute correct derivative HOT 3
- Incorrect Hessian by `exp` function HOT 1
- Method ambiguities reported by Aqua HOT 3
- Document internals? HOT 1
- Bug (NaNs) when differentiating eigenvectors of Symmetric matrices
- Error requiring `Symbolics` from `Optimization` HOT 1
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